Self-Stressing State and Progressive Limit Method Study of a Flat Strip DOI
Leonid Stupishin, E. Nikitin, Maria L. Moshkevich

и другие.

Lecture notes in civil engineering, Год журнала: 2024, Номер unknown, С. 349 - 357

Опубликована: Дек. 31, 2024

Язык: Английский

Data-driven compressive strength prediction of basalt fiber reinforced rubberized concrete using neural network-based models DOI
Chunhua Lü, Chenxi Zhou,

Siqi Yuan

и другие.

Materials Today Communications, Год журнала: 2025, Номер unknown, С. 111706 - 111706

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Experimental and machine learning approaches to investigate the properties of foamed concrete made with surkhi and dolomitic limestone as cement replacements DOI

Goyol Halima Aaron,

Md Azree Othuman Mydin, Dina E. Tobbala

и другие.

Multiscale and Multidisciplinary Modeling Experiments and Design, Год журнала: 2025, Номер 8(2)

Опубликована: Янв. 30, 2025

Язык: Английский

Процитировано

0

Assessing creep and creep recovery performance of plastic processed aggregate based concrete DOI Creative Commons
Fahad Alqahtani, Idrees Zafar

Scientific Reports, Год журнала: 2025, Номер 15(1)

Опубликована: Март 19, 2025

The use of plastic in concrete through various substitution approaches have been targeted last few decades with the main aim plummeting environmental loads construction industry. Although major mechanical and durability properties aggregate studied depth, petite data is available for its creep characteristics. Therefore, current study was designed to access recovery processed aggregates concretes. Five mixes consisting at replacement levels 0%, 25%, 50%, 75% 100% were developed w/c 0.5. tests conducted on all specimens determine evaluate a period approx. three years. augmentation resulted amplification instantaneous strain, ultimate shrinkage strain concrete. An increase 100, 119 69% noted total substitution. increased by 30.1, 96.8% 25% respectively. Overall it noticed that decrease compressive strength strains as compared reference mix. results from this experimental advocate specifically non-structural application requiring flexible solution.

Язык: Английский

Процитировано

0

Enhancing Mechanical Performance of Glass Fiber Reinforced Gypsum Composites with Carbon Black and Magnetite: An Integrated Optimization Approach DOI
Sadık Alper Yildizel, Abdurrahim Toktaş, Ülkü Sultan Keskin

и другие.

Journal of Building Engineering, Год журнала: 2025, Номер unknown, С. 112962 - 112962

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0

Feasibility of low cost upcycling uncleaned waste glass as poorly graded fine aggregate (UPGWGFA) in concrete construction DOI
Kameshwar Sahani, Avik Kumar Das,

Anish Kunwar

и другие.

Construction and Building Materials, Год журнала: 2025, Номер 486, С. 141962 - 141962

Опубликована: Май 29, 2025

Язык: Английский

Процитировано

0

Development of Ultra High-Performance Concrete with Artificial Aggregates from Sesame Ash and Waste Glass: A Study on Mechanical Strength and Durability DOI Creative Commons
A. Rezzoug, Ali H. AlAteah, Muwaffaq Alqurashi

и другие.

Buildings, Год журнала: 2025, Номер 15(11), С. 1942 - 1942

Опубликована: Июнь 4, 2025

This study demonstrates the conversion of agricultural and industrial waste into construction materials by developing ultra-high-performance concrete using cold-bonded sesame ash glass aggregates. The primary focus this was sustainability valorization in self-curing systems. focuses on many aspects producing cementless with superior short- long-term properties, incorporating an innovative artificial aggregate premanufactured glass. Prepacking technology casting used. A additive is used to reduce energy required for curing. In aggregates (CBAs), content ranged from 10 50% total sand volume. Polyethylene glycol as internal curing agent evaluate mechanical properties concrete, including compressive strength tensile at different ages. durability characteristics were also analyzed terms its resistance sulfates, chloride ion penetration, performance elevated temperatures 300 600 °C. Microscopic analyses conducted scanning electron microscopy (SEM), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), Differential Scanning Calorimetry (DSC). results showed a significant improvement performance, especially 30%, which resulted highest 147.2 MPa 90 days. 11.93% increase compared that reference mix. improved 14.5% same replacement ratio. mix containing 30% manufactured demonstrated best thermal resistance, retaining percentage residual both °C °C, well sulfate impact reduction factor 39.5%. When ratio increased 50%, penetration significantly 41% FTIR, TGA, DSC enhanced silicate polymerization carbonate formation, contributing chemical stability density matrix.

Язык: Английский

Процитировано

0

Enhancing the predictive accuracy of recycled aggregate concrete’s strength using machine learning and statistical approaches: a review DOI
Jawad Tariq,

Kui Hu,

Syed Tafheem Abbas Gillani

и другие.

Asian Journal of Civil Engineering, Год журнала: 2024, Номер unknown

Опубликована: Окт. 17, 2024

Язык: Английский

Процитировано

1

Modelling and evaluation of mechanical performance and environmental impacts of sustainable concretes using a multi-objective optimization based innovative interpretable artificial intelligence method DOI
Muhammed Ulucan, Güngör Yıldırım, Bilal Alataş

и другие.

Journal of Environmental Management, Год журнала: 2024, Номер 372, С. 123364 - 123364

Опубликована: Ноя. 16, 2024

Язык: Английский

Процитировано

1

Predictive Methods for the Evolution of Oil Well Cement Strength Based on Porosity DOI Creative Commons
Yuhao Wen,

Zi Chen,

Yuxuan He

и другие.

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Авг. 28, 2024

Abstract The oil well cement undergoes various physical and chemical changes during the hydration process, leading to formation of pores different sizes within stone. These can affect mechanical properties In civil engineering field, extensive attempts have been made predict concrete based on pore parameters, yielding good results. This paper explores in detail methods for predicting strength porosity size distribution. Through referencing prediction engineering, distribution are used as parameters. accuracy predictions by empirical models deep learning is compared, it concluded that neither formulas nor ordinary provide accurate fitting However, due optimization its algorithm structure, KAN model give more pore-size-strength relationship Additionally, quantitative between stone explored. application provides strong guidance monitoring optimizing cementing quality construction process.

Язык: Английский

Процитировано

0

Evaluation of Machine Learning and Traditional Methods for Estimating Compressive Strength of UHPC DOI Creative Commons
Tianlong Li,

Pengxiao Jiang,

Yunfeng Qian

и другие.

Buildings, Год журнала: 2024, Номер 14(9), С. 2693 - 2693

Опубликована: Авг. 28, 2024

This research provides a comparative analysis of the optimization ultra-high-performance concrete (UHPC) using artificial neural network (ANN) and response surface methodology (RSM). By ANN RSM, yield UHPC was modeled optimized as function 22 independent variables, including cement content, compressive strength, type, strength class, fly-ash, slag, silica-fume, nano-silica, limestone powder, sand, coarse aggregates, maximum aggregate size, quartz water, super-plasticizers, polystyrene fiber, fiber diameter, length, steel curing time. Two statistical parameters were examined based on their modeling, i.e., determination coefficient (R2) mean square error (MSE). RSM evaluated for predictive generalization capabilities different dataset from previously published research. Results show that is computationally efficient easy to interpret, whereas more accurate at predicting characteristics due its nonlinear interactions. model (R = 0.95 R2 0.91) 0.94, 0.90) can predict strength. The prediction optimal an 3.5% 7%, respectively. According model’s sensitivity analysis, water have significant impact

Язык: Английский

Процитировано

0